Save random values from multi-dimensional NumPy array

I have an 149x5 NumPy array. I need to save some (30%) of values selected randomly from whole array. Additionally selected values will be deleted from data.

What I have so far:

# Load dataset
data = pd.read_csv('iris.csv')

# Select randomly 30%(45) of rows from dataset
random_rows = data.sample(45)

# Object for values to be saved
values = []

# Iterate over rows and select a value randomly.
for index, row in data.iterrows():

   # Random between 1 - 5
   rand_selector = randint(0, 4)

   # Somehow save deleted value and its position in data object
   value = ??                                                 <-------

   values.append(value)

   # Delete random value
   del row[rand_selector]

To add further, the data from value will later be compared to values imputed in its place by other methods(data imputation), therefore I need the position of the deleted value in original dataset.